Electrocardiagram (ecg) processor

ABSTRACT

An electrocardiogram (ECG) processor is disclosed. The ECG processor includes ECG sampling circuitry configured in a first mode to acquire a continuous ECG sample set from an ECG signal by digitally sampling the ECG signal at a Nyquist rate for a first predetermined number of heartbeats and in a second mode to acquire a non-continuous ECG sample set from the ECG signal for a second predetermined number of heartbeats by digitally sampling active regions of the ECG signal that contain a PQRST complex and not from silent regions between adjacent PQRST complexes. The ECG processor also includes processing circuitry configured to determine from the continuous ECG sample set relative locations of the active regions and provide the relative locations of the active regions to the ECG sampling circuitry for sampling the ECG signal in the second mode.

RELATED APPLICATIONS

This application is related to U.S. Pat. No. 9,717,438, issued Aug. 1,2017, and titled MEDICAL DEVICE FOR DETECTING A VENTRICULAR ARRHYTHMIAEVENT; U.S. patent application Ser. No. 15/616,069, filed Jun. 7, 2017,and titled MEDICAL DEVICE AND METHOD FOR DETECTING A VENTRICULARARRHYTHMIA EVENT; and U.S. patent application Ser. No. 14/926,554, filedOct. 29, 2015, and titled MEDICAL DEVICE HAVING AUTOMATED ECG FEATUREEXTRACTION, the disclosures of which are hereby incorporated herein byreference in their entireties.

GOVERNMENT SUPPORT

This invention was made with government funds under contract number2013-HJ-2440 awarded by the ATIC-SRC Center for Energy EfficientElectronic Systems. The U.S. Government may have rights in thisinvention.

FIELD OF THE DISCLOSURE

The present disclosure relates to biomedical devices and methods usableto monitor electrocardiogram signals.

BACKGROUND

The electrical activity of the heart is presented by the surfaceelectrocardiogram (ECG) signal. Due to ease of use and non-invasiveness,the ECG is used as a prime tool not only to monitor the functionality ofthe heart but also to diagnose cardiac arrhythmia by extractinginformation about intervals, amplitudes, and wave morphologies such asP, QRS, and T-waves. Extracted features from the ECG signal play anessential role in diagnosing many cardiac diseases. Moreover, medicaldevices have been developed that are wearable by patients or areimplantable in patients to automatically monitor the ECG signal and takea predetermined action. For example, a wearable medical device mayinterface with a smartphone to remotely report an abnormal ECG to amedical professional, and an implantable medical device may beconfigured to apply a shock treatment to the patient's heart if anarrhythmia is detected. Both wearable and implantable medical devicesare battery powered. Therefore, a critical requirement for both wearableand implantable medical devices is energy efficiency, which in part isrelated to data collection and storage efficiency. Traditional wearableand implantable medical devices that monitor the ECG signal from apatient's heart completely digitize the ECG signal while using datacompression techniques. However, because regions within the ECG signalof no diagnostic value are processed during each heartbeat, thesetraditional wearable and implantable medical devices provide lessoverall energy efficiency than desired. Thus, an implantable medicaldevice and method that provides greater energy efficiency whileprocessing an ECG signal is needed.

SUMMARY

An electrocardiogram (ECG) processor is disclosed. The ECG processorincludes ECG sampling circuitry configured in a first mode to acquire acontinuous ECG sample set from an ECG signal by digitally sampling theECG signal at a Nyquist rate for a first predetermined number ofheartbeats and in a 20 second mode to acquire a non-continuous ECGsample set from the ECG signal for a second predetermined number ofheartbeats by digitally sampling active regions of the ECG signal thatcontain a PQRST complex and not from silent regions between adjacentPQRST complexes. The ECG processor also includes processing circuitryconfigured to determine from the continuous ECG sample set relativelocations of the active regions and provide the relative locations ofthe active regions to the ECG sampling circuitry for sampling the ECGsignal in the second mode.

In some exemplary embodiments, the ECG processor further includes amemory configured to store the non-continuous ECG sample set. Moreover,some exemplary embodiments include an active regions reconstructioncircuitry implementation of the smoothed L0 algorithm to reconstruct theECG signal from the non-continuous ECG sample set. Yet other exemplaryembodiments include firmware that when invoked performs the smoothed L0algorithm to generate data from the non-continuous ECG sample set forreconstruction of the ECG signal.

Those skilled in the art will appreciate the scope of the presentdisclosure and realize additional aspects thereof after reading thefollowing detailed description of the preferred embodiments inassociation with the accompanying drawing figures.

BRIEF DESCRIPTION OF THE DRAWING FIGURES

The accompanying drawing figures incorporated in and forming a part ofthis specification illustrate several aspects of the disclosure and,together with the description, serve to explain the principles of thedisclosure.

FIG. 1 is a depiction of an electrocardiogram (ECG) signal that isprocessed in accordance with the present disclosure.

FIG. 2 is a flowchart for an automated adaptive compressive sensingtechnique that is implemented by an ECG processor of the presentdisclosure.

FIG. 3 is a depiction of an ECG signal reconstructed from an activeregions-only sample set acquired by way of the automated adaptivecompressive sensing technique in accordance with the present disclosure.

FIG. 4 is a depiction of a system-on-chip (SOC) embodiment of the ECGprocessor that provides automatic adaptive compressive sensing of an ECGsignal in accordance with the present disclosure.

FIG. 5 is a depiction of an SOC that is an alternative embodiment of theECG processor that provides automated adaptive compressive sensing of anECG signal in accordance with the present disclosure.

DETAILED DESCRIPTION

The embodiments set forth below represent the necessary information toenable those skilled in the art to practice the embodiments andillustrate the best mode of practicing the embodiments. Upon reading thefollowing description in light of the accompanying drawing figures,those skilled in the art will understand the concepts of the disclosureand will recognize applications of these concepts not particularlyaddressed herein. It should be understood that these concepts andapplications fall within the scope of the disclosure and theaccompanying claims.

It will be understood that, although the terms first, second, etc. maybe used herein to describe various elements, these elements should notbe limited by these terms. These terms are only used to distinguish oneelement from another. For example, a first element could be termed asecond element, and, similarly, a second element could be termed a firstelement, without departing from the scope of the present disclosure. Asused herein, the term “and/or” includes any and all combinations of oneor more of the associated listed items.

It will be understood that when an element such as a layer, region, orsubstrate is referred to as being “on” or extending “onto” anotherelement, it can be directly on or extend directly onto the other elementor intervening elements may also be present. In contrast, when anelement is referred to as being “directly on” or extending “directlyonto” another element, there are no intervening elements present.Likewise, it will be understood that when an element such as a layer,region, or substrate is referred to as being “over” or extending “over”another element, it can be directly over or extend directly over theother element or intervening elements may also be present. In contrast,when an element is referred to as being “directly over” or extending“directly over” another element, there are no intervening elementspresent. It will also be understood that when an element is referred toas being “connected” or “coupled” to another element, it can be directlyconnected or coupled to the other element or intervening elements may bepresent. In contrast, when an element is referred to as being “directlyconnected” or “directly coupled” to another element, there are nointervening elements present.

Relative terms such as “below” or “above” or “upper” or “lower” or“horizontal” or “vertical” may be used herein to describe a relationshipof one element, layer, or region to another element, layer, or region asillustrated in the Figures. It will be understood that these terms andthose discussed above are intended to encompass different orientationsof the device in addition to the orientation depicted in the Figures.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the disclosure.As used herein, the singular forms “a,” “an,” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises,”“comprising,” “includes,” and/or “including” when used herein specifythe presence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

Unless otherwise defined, all terms (including technical and scientificterms) used herein have the same meaning as commonly understood by oneof ordinary skill in the art to which this disclosure belongs. It willbe further understood that terms used herein should be interpreted ashaving a meaning that is consistent with their meaning in the context ofthis specification and the relevant art and will not be interpreted inan idealized or overly formal sense unless expressly so defined herein.

FIG. 1 is a depiction of an exemplary electrocardiogram (ECG) signalthat is processed in accordance with the present disclosure. The ECGsignal is an electrical signal having voltage modulation that indicatesa first heartbeat and a second heartbeat. As shown in FIG. 1, the ECGsignal is divided into active regions and silent regions. Information ofinterest about the first heartbeat and second heartbeat indicated by theECG signal is contained within the active regions. The silent regionsare not completely silent in an electrical sense, but the silent regionstypically do not contain information of interest. Therefore, the presentdisclosure treats the silent regions as if they were completely silentfrom an ECG diagnostics point of view.

The information of interest within the active regions are onset of theP-wave P_(ON), the P-wave, the Q peak, the R peak, the S peak, theT-wave, and the end of the T-wave T_(OFF). The onset of the P-waveP_(ON), the Q peak, the R peak, the S peak, and the end of the T-waveT_(OFF) make up a PQRST complex. To capture the information of interest,a portion of the ECG signal within the active region is sampled. Inaccordance with the present disclosure, active regions are defined to bebetween the onset of the P-wave P_(ON) and the end of the T-wave T_(OFF)of an individual heartbeat such as the first heartbeat and the secondheartbeat. Also, in accordance with the present disclosure, silentregions are defined to be between the end of the T-wave T_(OFF) of aproceeding heartbeat such as the first heartbeat and the beginning ofthe P-wave P_(ON) of a next heartbeat such as the second heartbeat.

Restricting data acquisition, i.e., sampling of ECG signals to only theactive regions of ECG signals reduces the number of bytes of a memorychip used to store digital samples of the ECG signal. Moreover, if thelocations of the active regions are known, a compressive sensingtechnique can be employed to further greatly reduce the number of bytesof a memory chip used to store digital samples of the ECG signal.However, accurately locating the active regions using compressivesensing is not reliable. Therefore, the present disclosure employsNyquist rate sampling of the ECG signal for a first predetermined numberof heartbeats to provide an average relative location of the activeregions within the ECG signal. Once an average relative location of theactive regions is determined, compressive sensing is employed to acquirea minimal number of ECG signal samples from the active regions thatallows a faithful reproduction of the ECG signal using the minimal ECGsignal samples. This combination of Nyquist sampling and compressivesensing provides a unique automated adaptive compressive sensingtechnique that provides compression ratios between Nyquist sampling andcompressive sampling of at least 3.2:1, which is greater thancompression ratios realized by employing compressive sensing alone.

FIG. 2 is a flowchart for an automated adaptive compressive sensingtechnique that is implemented by an ECG processor of the presentdisclosure. ECG signal processing begins with acquiring a continuous ECGsample set from an ECG signal sampled at a Nyquist rate for a firstpredetermined number of heartbeats (step 2). In an exemplary embodiment,the first predetermined number of heartbeats is between three and fiveheartbeats. Next, the ECG processor determines relative locations ofactive regions and silent regions of the ECG signal from the continuousECG sample set (step 4). The ECG processor may process the continuousECG sample set using an ECG signal delineation technique such as the Panand Tompkins QRS complex detection algorithm. Next, the ECG processorthen acquires an active regions-only sample set by way of compressivesensing sampling using an average relative location of the activeregions for each of a second predetermined number of heartbeats (step6). The ECG processor determines the average relative location of theactive regions by averaging the active region located in step 5. In someembodiments, the second predetermined number of heartbeats is between 8and 16 heartbeats. The ECG processor then repeats steps 2-6 until adesired number of heartbeats have been processed. At that point, the ECGprocessor may reconstruct the ECG signal from the active regions-onlysample set using the smoothed L0 algorithm for finding the sparsestsolutions of an undetermined system of linear equations associated witha matrix loaded with the active regions-only sample set including afixed value for the silent regions (step 8).

FIG. 3 is a depiction of an ECG signal reconstructed from an activeregions-only sample set acquired by way of the automated adaptivecompressive sensing technique of FIG. 2. The reconstructed ECG signal ofFIG. 3 shows that the ECG processor provides fixed sample values forreconstructed silent regions. In some embodiments, the fixed samplevalue is equal to the last sample value of a previously reconstructedactive region.

FIG. 4 is an embodiment of an ECG processor in the form of asystem-on-chip (SOC) 10 that provides automatic adaptive compressivesensing of an ECG signal in accordance with the present disclosure. TheSOC 10 may be implemented with technologies such as field-programmablegate arrays, application-specific integrated circuits, digital signalprocessors, and combinations thereof.

The SOC 10 includes electronic digital logic gates and may includeelectronic amplifiers with active and passive filtering. In particular,the SOC 10 has ECG sampling circuitry 12 that includes a Nyquist ratesampler 14 and a compressive sensing sampler 16. In exemplaryembodiments, the Nyquist rate sampler 14 has an analog-to-digitalconverter configured to sample the ECG signal at a Nyquist rate F0. Atypical Nyquist rate F0 for sampling an ECG signal is 250 Hz.

The Nyquist rate sampler 14 has a first analog input 18 through whichthe ECG signal is received. The Nyquist rate sampler 14 further includesa first digital output 20 through which digitized samples of the ECGsignal are provided for further processing. The Nyquist rate sampler 14also includes a first control input 22 that enables and disables Nyquistrate sampling of the ECG signal. In exemplary embodiments, the firstcontrol input 22 receives binary logic signals such as a logic one and alogic zero. An example of a logic one may be a predefined voltage levelsuch as 1 V and an example of a logic zero may be a predefined voltagelevel such as 0 V. The Nyquist rate sampler 14 is responsive to binarylogic signals used to enable and disable the Nyquist sampling of the ECGsignal arriving at the first analog input 18. For example, an enablesignal such as a logic one arriving at the first control input 22 causesthe Nyquist rate sampler 14 to provide digitized samples of the ECGsignal through the first digital output 20. A disable signal such as alogic zero arriving at the first control input 22 causes the Nyquistrate sampler 14 to stop providing digitized samples of the ECG signalthrough the first digital output 20. In exemplary embodiments, theNyquist rate sampler 14 is placed in a first low power mode when adisable signal arrives at the first control input 22.

In exemplary embodiments, the compressive sensing sampler 16 has ananalog-to-digital converter that samples predetermined portions of theECG signal at a fraction of the Nyquist rate F0. However, it is to beunderstood that in some embodiments, the analog-to-digital converter ofthe compressive sensing sampler 16 is the same analog-to-digitalconverter of the Nyquist rate sampler 14. In such embodiments, at leastone of the control signals that enables and disables either of theNyquist rate sampler 14 or the compressive sensing sampler 16 may alsoset a sample rate of the analog-to-digital converter.

In other exemplary embodiments, the Nyquist rate sampler 14 and thecompressive sensing sampler 16 may each have dedicated analog-to-digitalconverters with fixed sampling rates. For example, the Nyquist ratesampler 14 may have a first dedicated analog-to-digital converter havinga sampling rate fixed at the Nyquist rate F0, and the compressivesensing sampler 16 may have a second analog-to-digital converter with aslower sampling rate fixed at a fraction of the Nyquist sampling rateF0. In exemplary embodiments, the fraction of the Nyquist rate F0 isequal to F0 divided by a compression ratio. An exemplary compressionratio in accordance with the present disclosure is 3.2:1. Thus, in anexemplary embodiment, a compressive sensing sampling rate is 250 Hz/3.2or 78 Hz.

The compressive sensing sampler 16 has a second analog input 24 throughwhich the ECG signal is received. The compressive sensing sampler 16further includes a second digital output 26 through which compressivesensing samples of the active region of the ECG signal are provided. Thecompressive sensing sampler 16 also includes a second control input 28that enables and disables the compressive sensing sampling rate of theECG signal. In exemplary embodiments, the first control input 22receives binary logic signals such as a logic one and a logic zero. Thecompressive sensing sampler 16 is responsive to binary logic signalsused to enable and disable the compressive sensing sampling of the ECGsignal arriving at the second analog input 24. For example, an enablesignal such as a logic one arriving at the second control input 28causes the compressive sensing sampler 16 to provide digitized samplesof the active region of the ECG signal through the second digital output26. A disable signal such as a logic zero arriving at the second controlinput 28 causes the compressive sensing sampler 16 to stop providingdigitized samples of the active region of the ECG signal through thesecond digital output 26. In exemplary embodiments, the compressivesensing sampler 16 is placed in the first low power mode when a disablesignal arrives at the second control input 28.

The compressive sensing sampler 16 further includes a digital signalinput 30 that receives a digital signal that provides an averagelocation and duration of active regions of the ECG signal. Thecompressive sensing sampler 16 uses the average location and duration ofthe active regions to schedule a start time and stop time for eachactive region undergoing compressive sensing sampling. A silent regionin which no samples are taken is defined as being between the stop timeof a previous active region and the start time of a next active region.An exemplary start time is the average onset of a P-wave P_(ON), and anexemplary stop time is the average end time of a T-wave T_(OFF).

The compressive sensing sampler 16 may generate a first increment signalthat indicates that the compressive sensing sampler 16 has encountered anew active region. The first increment signal is provided through afirst increment output 32.

A compressive sensing heartbeats counter 34 is responsive to the firstincrement signal. A first increment input 36 is coupled to the firstincrement output 32 of the compressive sensing sampler 16. Thecompressive sensing heartbeats counter 34 includes a first countregister COUNT_1 that is incremented by one for every active region thatthe compressive sensing sampler 16 encounters. The compressive sensingheartbeats counter 34 further includes a counter overflow output 38 thatis coupled to the second control input 28 of the compressive sensingsampler 16. In operation, the compressive sensing heartbeats counter 34generates an overflow signal when the first count register COUNT_1overflows when the number of active regions encountered by thecompressive sensing sampler 16 reaches a number greater than apredetermined number N. In an exemplary embodiment, the predeterminednumber N is set to between 8 and 16.

The overflow signal disables the compressive sensing sampler 16. A zerosignal is generated by the compressive sensing heartbeats counter 34when the first count register COUNT_1 is reset to zero. The zero signalis provided through the overflow output 38. The compressive sensingsampler 16 is enabled by the zero signal. The compressive sensingheartbeats counter 34 also includes a reset zero input 40 that receivesa reset zero signal that resets the first count register COUNT_1 tozero.

Nyquist processing circuitry 42 has an ECG peaks locator 44 thatdetermines locations of onset of the P-wave P_(ON), the P-wave, the Qpeak, the R peak, the S peak, the T-wave and the end of the T-waveT_(OFF). The ECG peaks locator 44 has a Nyquist samples input 46 that iscoupled to first digital output 20 of the Nyquist rate sampler 14. TheECG peaks locator 44 receives a continuous ECG sample set through theNyquist samples input 46. In an exemplary embodiment, the ECG peakslocator 44 processes the continuous ECG sample set using the Pan andTompkins QRS complex detection algorithm. In other words, the Nyquistprocessing circuitry 42 determines the relative locations of the activeregions by implementing a Pan and Tompkins QRS complex search throughthe continuous ECG sample set. The ECG peaks locator 44 may generate asecond increment signal each time the ECG peaks locator 44 locates a QRScomplex associated with a heartbeat. The second increment signal isprovided through a second increment output 48.

The Nyquist processing circuitry 42 further includes an active regionsdefiner 50 that defines boundaries of the active regions. The activeregions definer 50 receives locations of peaks located by the ECG peakslocator 44 and determines an average location of the onset of the P-waveP_(ON) and an average location of the end of the T-wave T_(OFF). Theactive region is defined as the average location of the onset of theP-wave P_(ON) to the average location of the end of the T-wave T_(OFF).These defined boundaries of the average active region are passed to thecompressive sensing sampler 16 though a boundaries output 52 that iscoupled to the digital signal input 30.

A Nyquist heartbeats counter 54 has a second increment input 56 and iscoupled to the second increment output 48 of the ECG peaks locator 44.The Nyquist heartbeats counter 54 is responsive to the second incrementsignal generated by the ECG peaks locator 44.

The Nyquist heartbeats counter 54 includes a second count registerCOUNT_2 that is incremented by one for every heartbeat that the ECGpeaks locator 44 locates. For example, in this exemplary embodiment, theECG peaks locator 44 generates second increment signal at an instant anR peak is located. The Nyquist heartbeats counter 54 further includes asecond counter overflow output 58 that is coupled to both the firstcontrol input 22 of the Nyquist rate sampler 14 and the reset zero input40. In operation, the Nyquist heartbeats counter 54 generates anoverflow signal when the second count register COUNT_2 overflows whenthe number of heartbeats processed by the ECG peaks locator 44 reaches anumber greater than a predetermined number M. In an exemplaryembodiment, the predetermined number M is set to between 3 and 5. TheNyquist heartbeats counter 54 also includes a reset zero input 60 thatreceives the reset zero signal that resets the second count registerCOUNT_2 to zero.

The SOC 10 further includes a memory 62 for storing compressive sensingsamples generated by the compressive sensing sampler 16. Examples ofmemory types suitable for the memory 62 include but are not limited tostatic random access memory (SRAM) and non-volatile memory such as flashmemory. The memory 62 has a first digital input 64 that is coupled tothe second digital output 26 of the compressive sensing sampler 16. Inan exemplary embodiment, compressive sensing samples arriving at thefirst digital input 64 are automatically stored sequentially in memorylocations within the memory 62. Compressive sensing samples storedwithin the memory 62 are retrieved by user applications through a memoryoutput 66.

In an exemplary embodiment, the SOC 10 further includes an active regionreconstruction circuitry 68 that is a hardware implementation of areconstruction algorithm such as the smoothed L0 algorithm used to findthe sparsest solutions of an undetermined system of linear equationsassociated with the compressive sensing samples. The active regionreconstruction circuitry 68 has second digital input 70 that is coupledto the memory output 66. Digital data making up reconstructed ECGsignals is available to user applications through a third digital output72.

FIG. 5 is a depiction of an SOC 74 that is an alternative embodiment ofthe ECG processor that provides automatic adaptive compressive sensingof the ECG signal in accordance with the present disclosure. The SOC 74includes an input/output interface 76 for receiving an analog-type ECGsignal from ECG sensor circuitry. The input/output interface 76 mayamplify and filter the ECG signal in order to provide a conditioned ECGsignal. It is to be understood from the exemplary embodiment of FIG. 5that the input/output interface 76 is configured to interface with bothdigital signals and analog signals.

ECG sampling circuitry 78 receives and samples the conditioned ECGsignal in two modes. In a first mode the ECG sampling circuitry 78acquires a continuous ECG sample set from the conditioned ECG signal bydigitally sampling the conditioned ECG signal at a Nyquist rate for afirst predetermined number of heartbeats. In a second mode that performsa type of compressive sensing, the ECG sampling circuitry 78 acquires anon-continuous ECG sample set that is made up of compressive sensingsamples.

In at least one exemplary embodiment, the first predetermined number ofheartbeats is between three and five heartbeats and a secondpredetermined number of heartbeats is between 8 and 16 heartbeats.However, it is to be understood that the first predetermined number ofheartbeats and the second number of predetermined heartbeats areselectable to higher or lower than the exemplary embodiment depending onchanges in heart rate from lower to higher and vice versa. Moreover, theECG sampling circuitry is configured to sample the active regions of theECG signal that contain the PQRST complex in the second mode at a slowerrate than the Nyquist rate. In exemplary embodiments, the slower rate isequal to the Nyquist rate divided by a compression ratio. In at leastsome exemplary embodiments, the compression ratio is between 2.6:1 and3.2:1. As such, for a Nyquist rate of 250 Hz the slower rate is 78 Hzfor a compression ratio of 3.2:1.

A central processing unit 80 controls the mode in which the ECG samplingcircuitry operates, processes the sampled ECG signal, and directs ECGdata flow. In order to provide appropriate mode control, the centralprocessing unit 80 initially receives a portion of the sampled ECGsignal from the ECG sampling circuitry 78 operating in the first modethat samples the conditioned ECG signal at the Nyquist rate for thefirst predetermined number of heartbeats to provide the centralprocessing unit 80 with a continuous ECG sample set.

The central processing unit 80 then processes the continuous ECG sampleset to determine relative locations of the active regions. In anexemplary embodiment, the central processing unit 80 processes thecontinuous ECG sample set using the Pan and Tompkins QRS complexdetection algorithm. Once the relative locations of the active regionshave been determined, the central processing unit indicates to the ECGsampling circuitry 78 the relative locations of the active regions andchanges the mode of the ECG sampling circuitry 78 to the second modethat acquires the non-continuous ECG sample set from the ECG signal forthe second predetermined number of heartbeats.

A memory 82 receives the non-continuous ECG sample set as digital ECGdata that is stored within a data storage block of the memory 82. Thememory 82 can be a non-volatile random access memory (NVRAM) such asflash memory, or the memory 82 can be static RAM (SRAM) or a combinationof NVRAM and SRAM. In the latter case, instructions executed by thecentral processing unit 80 may be stored as firmware in the NVRAM and/ortransferred from NVRAM to a block of program memory made up of SRAM. Inat least some embodiments, the firmware may be updated through theinput/output interface 76.

External applications may access the digital ECG data stored within thememory 82 for the digital ECG data by sending a request to the centralprocessing unit 80 through the input/output interface 76. Upon receivingthe request, the central processing unit 80 retrieves the digital ECGdata and passes the ECG digital data through the input/output interface76, which may provide level shifting and handshaking with devices thatare controlled by the user applications.

Alternatively, the central processing unit 80 may reconstruct the activeregions of the ECG signal by executing a reconstruction algorithm suchas the smoothed L0 algorithm used to find the sparsest solutions of anundetermined system of linear equations associated with the compressivesensing samples of the non-continuous ECG sample set. In at least oneexemplary embodiment, the central processing unit 80 generates areconstructed ECG signal by processing the non-continuous ECG data usinga smoothed L0 algorithm to reconstruct active regions and substitutefixed values for the silent regions between adjacent active regions.

An exemplary user application is a medical implantable wireless sensornode (WSN) application. The medical implantable WSN application takesadvantage of the compression ratio of at least 3.2:1, a correlationcoefficient of 98%, and a percentage root mean square difference of atleast 7 that is provided by the performance of the exemplary embodimentof SOC 10 depicted in FIG. 4. In general, examples of user applicationsinclude but are not limited to battery-powered mobile health caredevices having ECG sensors, pacemakers, and health-relatedInternet-of-Things (IoT) devices.

Those skilled in the art will recognize improvements and modificationsto the preferred embodiments of the present disclosure. All suchimprovements and modifications are considered within the scope of theconcepts disclosed herein and the claims that follow.

What is claimed is:
 1. An electrocardiogram (ECG) processor comprising:ECG sampling circuitry configured in a first mode to acquire acontinuous ECG sample set from an ECG signal by digitally sampling theECG signal at a Nyquist rate for a first predetermined number ofheartbeats and in a second mode to acquire a non-continuous ECG sampleset from the ECG signal for a second predetermined number of heartbeatsby digitally sampling active regions of the ECG signal that contain aPQRST complex and not from silent regions between adjacent PQRSTcomplexes; and processing circuitry configured to determine from thecontinuous ECG sample set relative locations of the active regions andprovide the relative locations of the active regions to the ECG samplingcircuitry for sampling the ECG signal in the second mode.
 2. The ECGprocessor of claim 1 further including a memory configured to store thenon-continuous ECG sample set.
 3. The ECG processor of claim 1 whereinthe ECG sampling circuitry is configured to sample the active regions ofthe ECG signal that contain the PQRST complex in the second mode at aslower rate than the Nyquist rate.
 4. The ECG processor of claim 3wherein the slower rate is equal to the Nyquist rate divided by acompression ratio.
 5. The ECG processor of claim 4 wherein thecompression ratio is between 2.6 and 3.2.
 6. The ECG processor of claim4 wherein the Nyquist rate is 250 Hz and the slower rate is 78 Hz. 7.The ECG processor of claim 1 wherein the processor circuitry determinesthe relative locations of the active regions by implementing a Pan andTompkins QRS complex search through the continuous ECG sample set. 8.The ECG processor of claim 1 wherein the first predetermined number ofheartbeats is between three and five heartbeats.
 9. The ECG processor ofclaim 1 wherein the second predetermined number of heartbeats is between8 and 16 heartbeats.
 10. The ECG processor of claim 1 wherein the firstpredetermined number of heartbeats is between three and five heartbeatsand the second predetermined number of heartbeats is between 8 and 16heartbeats.
 11. The ECG processor of claim 1 further configured togenerate reconstructed active regions from the non-continuous ECG dataset.
 12. The ECG processor of claim 7 further configured to substitutefixed values for silent regions between adjacent reconstructed activeregions to generate a reconstructed ECG signal.
 13. The ECG processor ofclaim 1 further configured to generate a reconstructed ECG signal byprocessing the non-continuous ECG data using a smoothed L0 algorithm toreconstruct active regions and substitute fixed values for the silentregions between adjacent active regions.
 14. The ECG processor of claim2 wherein the processing circuitry is a central processing unit (CPU).15. The ECG processor of claim 14 wherein a memory is further configuredto store CPU instructions that when executed by the CPU determine therelative locations of the active regions from the continuous ECG sampleset.
 16. The ECG processor of claim 15 wherein the CPU instructions aresoftware.
 17. The ECG processor of claim 16 wherein the CPU instructionsare firmware.
 18. The ECG processor of claim 1 wherein the ECG processoris a system-on-chip (SOC).
 19. The ECG processor of claim 18 wherein theSOC is at least partially implemented with field-programmable gate arraytechnology.
 20. The ECG processor of claim 18 wherein the SOC isimplemented as an application-specific integrated circuit.